The present invention relates to the diagnostic imaging arts. It finds particular application in conjunction with magnetic resonance angiography and will be described with particular reference thereto. However, the invention may find application in other imaging areas in which image values have a wide dynamic range and varying degrees of uncertainty associated with different pixel brightness levels.
In x-ray angiography, x-rays which pass through the patient are used to expose photographic film. One or more shadowgraphic or projection x-ray image is taken through a region of interest of the patient. In order to improve contrast between the patient's blood vessels and surrounding tissue, the patient is commonly injected with a contrast agent. The x-ray contrast agents commonly cause the patient's blood to attenuate the x-ray beam 200-300 times as much as comparable volumes of surrounding tissue. The resultant angiographic film image has a dark background where there are no blood vessels, and the blood vessels clearly delineated in white. There is a characteristic translucent appearance where blood vessels cross.
Analogous projection or shadowgraphic angiographic images can be created from magnetic resonance imaging. Most commonly, pixel values are determined for each pixel in a volumetric region defined by a plurality of parallel, planar magnetic resonance images. A viewing plane is defined outside of the volume orthogonal to a direction from which the radiologist wishes to view the material in the volume. The viewing direction is generally parallel to the direction that the x-ray beam would have been directed in x-ray angiography. The viewing plane is divided into pixels corresponding to pixels of a resultant video angiographic image and a ray is projected from each pixel orthogonal to the viewing plane (parallel to the viewing direction) into the volume. A value for each pixel of the image is derived from the brightness or voxel values of each voxel that the corresponding ray intersects as it passes through the volume region.
One difficulty with the magnetic resonance data is that the blood vessels are only 2 to 3 times as bright as the surrounding tissue. This small differentiation between the blood vessels and surrounding tissue causes the MR angiographic images to lack the definition and contrast characteristic of the x-ray angiographic images. The background tends to fade into gray tones. Of course, the blood vessels are not perfect tubes with a uniform brightness across. Rather, the blood vessels themselves have various gray scale shadings indicative of changes in contour, blockages, restrictions, and the like.
In one technique for imparting the visual image characteristics of an x-ray angiography image into a magnetic resonance angiography image, the pixel values along each projected ray are examined to find the pixel with the maximum intensity. This technique is often called the "Maximum Intensity Projection" or MIP technique. This causes the brightest object along each ray to be displayed on the resultant projection image at full intensity. This improved the brightness of the blood vessels. See Laub, et al., "3D MR Angiography Using Bipolar Gradient Echoes" SMRM Book of Abstracts, p. 52, 1987. The surrounding tissue also tends to become bright or more gray, reducing the blackness of the background.
By convention, the resultant angiographic image depicts the blood as bright or white, but not all the same brightness. Larger vessels tend to be brighter than smaller or thinner vessels. Background areas have a variety of gray scales. Some of the background areas are appropriately light gray due to the presence of blood flowing through very fine capillaries too small to be imaged as individual blood vessels. In other regions, light gray and even white spots are attributable to noise. The gray background problem compounds itself when the images are photographed on film to make a permanent record. The lack of contrast between the blood vessels and the background tissue renders film photography more difficult and produces photographic images which are more difficult to read and interpret.
Various techniques have been proposed for darkening the background. In one technique, the computer generated angiographic image is analyzed and a portion of the image which is clearly identifiable as blood is identified. The computer then, with pattern recognition and region growing techniques, attempts to follow the blood vessels through the imaged region. Once a complete mapping of the blood vessels is made, the remaining pixels can be set to black. One problem with pattern mapping or region growing approaches is that they are very computer intensive. Very large computers with very long computing times are required to process each image. Moreover, although they can follow large blood vessels quite accurately, the computer routines have difficulty with small blood vessels. The computer routines have difficulty deciding whether or not smaller blood vessels are in fact blood vessels. The computer tends to decide that many smaller blood vessels are not blood vessels and not follow them. The smaller blood vessels are then inappropriately set to black, causing a misrepresentation of what could be significant medical information.
In one particular implementation, the volumetric data are processed with a connected-voxel algorithm. A low signal intensity threshold is used to separate groups of voxels associated with different vessels from one another and to remove the contribution from low intensity stationary, non-blood material. The remaining voxels are grouped by a connectivity criterion into discrete objects. Vessels are represented by three-dimensional objects. Unconnected small objects were discarded as being noise and not part of the circulatory system. See "Application of Connected-Voxel Algorithm to MR Angiographic Data", Saloner, et al., JMRI, pp. 423-430, 1991. This technique is again very computer intensive, requiring long processing times and tends to lose or omit the smaller blood vessels.
In another technique, angiographic images are obtained by ray projection techniques from a plurality of directions. Each voxel of the volumetric image is thus examined from several directions, e.g. three. If the same spot represents blood in all images, then it is taken as blood. If not, it is taken as noise and deleted. See "The Maximum Intensity Projection As a Segmentation Tool", Denison, et al., SMRI Book of Abstracts, pg. 73, Abstract 250, 1990. Of course, in order to view the object from three or more directions, at least three times the computing time is required to generate the angiographic image.
In another technique, the image data is operated upon by a Hough transform. The Hough transform maps voxels belonging to a given curve to a single point. Through this mapping, bright pixels which are part of a blood vessel laying along a curve can be differentiated from bright pixels which are merely a random incidence of noise. See "The Hough Transform Applied to 3D MRA Data Sets", Wood, et al., SMRI Book of Abstracts, page 158 Abstract PO84, 1990. However, this technique is again very computationally intensive, requiring long periods of time to process each image.
In accordance with the present invention, a new and improved technique is provided for generating angiographic images with a darkened background.